Search NASA⌕ Search

SEARCH · Search NASA

Results for “function composition”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11

Nanoparticle-Induced Disorder at Complex Liquid–Liquid Interfaces: Effects of Curvature and Compositional Synergy on Functional Surfaces

The self-assembly of surfactant monolayers at interfaces plays a sweeping role in tasks ranging from household cleaning to the regulation of the respiratory system. The synergy between different nanoscale species at an interface can yield assemblies with exceptional properties, which enhance or modulate their function. However, understanding the mechanisms underlying coassembly, as well as the effects of intermolecular interactions at an interface, remains an emerging and challenging field of study. Herein, we study the interactions of gold nanoparticles striped with hydrophobic and hydrophilic ligands with phospholipids at a liquid–liquid interface and the resulting surface-bound complexes. We show that these nanoparticles, which are themselves minimally surface active, have a direct concentration-dependent effect on the rapid reduction of tension for assembling phospholipids at the interface, implying molecular coassembly. Through the use of sum frequency generation vibrational spectroscopy, we reveal that nanoparticles impart structural disorder to the lipid molecular layers, which is related to the increased volumes that amphiphiles can sample at the curved surface of a particle. The results strongly suggest that hydrophobic and electrostatic attractions imparted by nanoparticle functionalization drive lipid–nanoparticle complex assembly at the interface, which synergistically aids lipid adsorption even when lipids and nanoparticles approach the interface from opposite phases. The use of tensiometric and spectroscopic analyses reveals a physical picture of the system at the nanoscale, allowing for a quantitative analysis of the intermolecular behavior that can be extended to other systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synergistic Enhancement of Electrocatalytic CO 2 Reduction with Gold Nanoparticles Embedded in Functional Graphene Nanoribbon Composite Electrodes

Regulating the complex environment accounting for the stability, selectivity, and activity of catalytic metal nanoparticle interfaces represents a challenge to heterogeneous catalyst design. Here in this paper, we demonstrate the intrinsic performance enhancement of a composite material composed of gold nanoparticles (AuNPs) embedded in a bottom-up synthesized graphene nanoribbon (GNR) matrix for the electrocatalytic reduction of CO 2 . Electrochemical studies reveal that the structural and electronic properties of the GNR composite matrix increase the AuNP electrochemically active surface area (ECSA), lower the requisite CO 2 reduction overpotential by hundreds of millivolts (catalytic onset > -0.2 V versus reversible hydrogen electrode (RHE)), increase the Faraday efficiency (>90%), markedly improve stability (catalytic performance sustained over >24 h), and increase the total catalytic output (>100-fold improvement over traditional amorphous carbon AuNP supports). The inherent structural and electronic tunability of bottom-up synthesized GNR-AuNP composites affords an unrivaled degree of control over the catalytic environment, providing a means for such profound effects as shifting the rate-determining step in the electrocatalytic reduction of CO 2 to CO, and thereby altering the electrocatalytic mechanism at the nanoparticle surface.

36 MATERIALS SCIENCE↗

Rapid data acquisition and machine learning-assisted composition design of functionally graded alloys via wire arc additive manufacturing

Abstract The lack of high-quality datasets in materials science hinders artificial intelligence (AI)-driven alloy design. To address this challenge, wire arc additive manufacturing (WAAM) was employed to fabricate graded alloys, generating extensive data for machine learning (ML)-assisted property prediction. ML models were developed using high-throughput experiments, computational models, and genetic algorithm to optimize feature selection, successfully predicting hardness and porosity. The ML model demonstrated its efficacy by designing a gradient alloy with enhanced properties. However, scaling up revealed uncertainties in tensile property and porosity due to differences in size and thermal conditions between the designed alloy build and the gradient print used to construct the ML model. This underscores the need for uncertainty quantification and process optimization in WAAM-driven alloy design. Our work advances AI-integrated additive manufacturing, offering a rapid approach to exploring process–structure–property relationships and accelerating materials development.

Wang, Xin↗

Composition and work function relationship in Os–Ru–W ternary alloys

Os–Ru thin films with varying concentrations of W were sputter deposited in order to investigate their structure–property relationships. The films were analyzed with x-ray diffraction to investigate their crystal structures, and a Kelvin probe to investigate their work functions. An Os–Ru–W film with ∼30 at. % W yielded a work function maximum of approximately 5.38 eV. These results align well with other studies that found work function minima from thermionic emission data on M-type cathodes with varying amounts of W in the coatings. Furthermore, the results are consistent with other work explaining energy-level alignment and charge transfer of molecules on metal oxides. This may shed light on the mechanism behind the “anomalous effect” first reported by Zalm et al., whereby a high work function coating results in a low work function for emitting cathode surfaces. An important implication of this work is the potential for the Kelvin probe to evaluate the effectiveness of dispenser cathode coatings.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Effect of in utero and lactational exposure to antiretroviral therapy on the gut microbial composition and metabolic function in aged rat offspring

Despite the highly effective impact of antiretroviral therapy (ART) in reducing mother-to-child transmission of human immunodeficiency virus (HIV), there are concerns of long-term impacts of ART on the health of the offspring. The implications of perinatal exposure to antiviral drugs on the gut bacterial population and metabolic function in the offspring is unclear but may influence health outcomes given the various reported effects of the microbiome in human health. This study aims to gain insight into the potential effect ofin uteroand lactational exposure to ART on gut microbiota populations and short‐chain fatty acids (SCFAs) production in aged rat offspring. Pregnant rats were administered a combination of antiretroviral drugs (abacavir/dolutegravir/lamivudine) at two different dose levels during gestation and throughout lactation, and the fecal bacterial abundance and SCFA levels of the offspring were analyzed when they reached 12 months of age. Our results showed dose-dependent and sex-based differences in fecal microbial abundance at various taxonomic levels. Specifically, we found a decline inFirmicutesin males, and an increase inActinobacteriaamong males and females. Furthermore, a sex-specific distribution reorganization ofLactobacillus,Bifidobacterium, andAkkermansiawas identified. No significant difference in the concentration of prominent SCFAs and IgA levels were identified. These findings provide preliminary information indicating the need to evaluate perinatal effects of ART more comprehensively on the gut bacterial and metabolic function in future studies, and their potential role in offspring health outcomes.

Research & Experimental Medicine↗

Mechanisms of Manganese(II) Oxidation by Filamentous Ascomycete Fungi Vary with Species and Time as a Function of Secretome Composition

Manganese (Mn) oxides are among the strongest oxidants and sorbents in the environment, and Mn(II) oxidation to Mn(III/IV) (hydr)oxides includes both abiotic and microbially-mediated processes. While white-rot Basidiomycete fungi oxidize Mn(II) using laccases and manganese peroxidases in association with lignocellulose degradation, the mechanisms by which filamentous Ascomycete fungi oxidize Mn(II) and a physiological role for Mn(II) oxidation in these organisms remain poorly understood. Here we use a combination of chemical and in-gel assays and bulk mass spectrometry to demonstrate secretome-based Mn(II) oxidation in three phylogenetically diverse Ascomycetes that is mechanistically distinct from hyphal-associated Mn(II) oxidation on solid substrates. We show that Mn(II) oxidative capacity of these fungi is dictated by species-specific secreted enzymes and varies with secretome age, and we reveal the presence of both Cu-based and FAD-based Mn(II) oxidation mechanisms in all 3 species, demonstrating mechanistic redundancy. Specifically, we identify candidate Mn(II)- oxidizing enzymes as tyrosinase in Stagonospora sp. SRC1lsM3a, bilirubin oxidase in Stagonospora sp. and Paraconiothyrium sporulosum AP3s5-JAC2a, and GMC oxidoreductase in all 3 species, including Pyrenochaeta sp. DS3sAY3a. Furthermore, we demonstrate that secretome-based Mn(II) oxidative capacity is induced by the presence of Mn(II) in Stagonospora sp. and Pyrenochaeta sp., suggesting a physiological role for Mn(II) oxidation in these Ascomycetes. The diversity of the candidate Mn(II)-oxidizing enzymes identified in this study suggests that the ability of fungal secretomes to oxidize Mn(II) may be more widespread than previously thought.

Zeiner, Carolyn A.↗

Landscape-scale Characterization of Arctic Tundra Vegetation Composition, Structure, and Function with a Multi-sensor Unoccupied Aerial System: Supporting Data.

Airborne remote sensing data collected using the Brookhaven National Laboratory's (BNL) heavy-lift unoccupied aerial system (UAS) octocopter platform, the Osprey, operated by the Terrestrial Ecosystem Science and Technology (TEST) group (https://www.bnl.gov/testgroup). This package includes data from three flights flown over the NGEE-Arctic Council, Kougarok and Teller sites in July, 2018. The Osprey is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface 'skin' temperature imagery, as well as surface reflectance at 1 nm intervals in the visible to near-infrared spectral range 350 - 1000 nm measured at regular intervals along each flight path. Derived image products include ortho-mosaiced RGB and TIR images, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, digital terrain model (DTM), and a canopy height model (CHM). In addition, a VNIR surface reflectance file is provided for the trigger locations collected during each flight campaign. Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Unprocessed and processed data products are included in this package (processing levels 0-3). Data and metadata are provided as text (*.txt, *.json, *.kml, *hdr, *.enp), tabular (*.dat, *.csv, *.waypoint, ENVI format (no extension)), point cloud (*.laz) and image (*.jpg, *.tif, *png) formats. This metadata document contains flight campaign, instrument and file metadata, along with a description of data processing levels, data products and file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy?s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Integrating very-high-resolution UAS data and airborne imaging spectroscopy to map the fractional composition of Arctic plant functional types in Western Alaska

Widespread changes in vegetation cover and composition are driving strong impacts on Arctic ecosystem functioning and global climate feedbacks. An accurate characterization of tundra vegetation composition is required to understand how the Arctic will respond to future climate change. However, quantifying tundra vegetation composition over large areas is challenging as commonly-used satellite observations are too coarse, spatially and spectrally, to differentiate low-lying tundra vegetation types. Recent airborne and spaceborne imaging spectroscopy platforms provide better data to characterize vegetation composition. Yet, our ability to characterize vegetation composition with imaging spectroscopy remains largely unexplored in the Arctic, particularly due to a lack of ground observations needed to train and test classification models. To address this problem, we collected very-high-resolution (VHR, ~5 cm) unoccupied aerial system (UAS) imagery at three low-Arctic tundra sites located on the Seward Peninsula, western Alaska. In this paper, we examine the feasibility of integrating imagery from the UAS and the hyperspectral Airborne Visible/Infrared Imaging Spectrometer, Next Generation (AVIRIS-NG) airborne instrument to map the fractional composition of 12 key Arctic plant functional types (PFTs). To this end, we first mapped the 12 PFTs from our VHR UAS imagery using random forest classification. We then used these UAS-derived PFT maps as ground truth to develop partial least squares regression (PLSR) models to predict the fractional cover (FCover) of each PFT from AVIRIS-NG imagery. Further, we evaluated the performance of our PLSR models using reserved UAS samples, as well as by mapping PFT FCover and dominant PFT for large tundra landscapes. Our results show that 1) Arctic PFTs can be effectively mapped using VHR UAS imagery, with overall accuracy between 86% and 92%, 2) when the UAS mapped PFTs were used to inform PLSR scaling models, the FCover of the 12 PFTs could be effectively estimated from AVIRIS-NG imagery with a mean absolute error (MAE) <0.13, and 3) our PLSR models outperformed traditional, fully constrained least-squares (FCLS) linear mixture analysis and produced high-quality, spatially contiguous PFT FCover and PFT maps that captured vegetation spatial patterns with similar accuracy to those developed from UAS imagery. The developed PLSR models have the potential to be broadly applied for quantifying vegetation composition with AVIRIS-NG images to help monitor tundra vegetation dynamics and improve process-based modeling of tundra ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Diazonium-Functionalized Silicon Hybrid Photoelectrodes: Film Thickness and Composition Effects on Photoelectrochemical Behavior

Aryl diazonium electrografting is a powerful method for imparting molecular functionality onto various substrates by forming a stable carbon-surface covalent bond. While the high reactivity of the aryl radical intermediate makes this method fast and reliable, it can also lead to the formation of an insulating and disordered multilayer film. These thick films affect electrochemical performance, especially for semiconductor substrates used in photoelectrochemical applications. For this work we studied the effects of film thickness and composition by electrografting in situ-generated aminobenzene diazonium salts onto both n-type and p-type silicon electrodes at fixed potentials. Next, we attached ferrocene to the amine-terminated films and probed their (photo)­electrochemical behavior. Cyclic voltammetry measurements showed decreased electrochemical reversibility with increasing diazonium film thickness; this reversibility was restored when ferrocene was incorporated throughout the film with a layer-by-layer deposition process. Finally, we compared the behavior of dark p-type electrodes to n-type photoelectrodes and observed differences in the electrochemical reversibility that we attribute to the change in potential drop across the two interfaces.

charge transfer↗

Local lattice distortions and the structural instabilities in bcc Nb–Ta–Ti–Hf high-entropy alloys: An ab initio computational study

Local lattice distortions (LLD) and structural stability of body-centered cubic (bcc) Nb–Ta–Ti–Hf high-entropy alloys (HEAs) are studied as functions of composition employing ab initio density-functional theory calculations, with specific focus on the role of the relative concentrations of group IV (Ti and Hf) versus group V (Nb and Ta) elements. Calculated results are presented as a function of composition x in Nb x Ta 0.25 Ti (0.75-x)/2 Hf (0.75-x)/2 alloys, for elastic moduli, phonon spectral functions, LLD and structural energy differences for the bcc and competing hexagonal close-packed (hcp) and ω phases. The results highlight the important role of group V elements and LLD in stabilizing the bcc structure. They further reveal how composition x can be tuned to alter both the magnitude of the LLD and structural energy differences. Specifically, the magnitude of the structural energy differences, and elastic and dynamic stability of the bcc phase, are enhanced with increasing x, while the LLD increase in magnitude as this concentration is decreased. The results also show evidence of correlated LLD at lower values of x, reflecting local structural distortions towards the ω phase, but not hcp. The degree of ω-collapse is nevertheless partial i.e., transformation towards this phase is not observed to be complete due to the presence of Ta and Nb. At lower values of x we further find an energy landscape characterized by multiple, nearly degenerate local energy minima for different values of the LLD.

36 MATERIALS SCIENCE↗

On-the-fly response function generation method for composite coarse mesh

The hybrid stochastic deterministic transport code COMET, based on the incident response expansion theory, is used to model reactor cores with high fidelity and formidable computational speed. COMET models a reactor core using a library of incident flux response expansion coefficients that are pre computed for all the unique lattice cells (e.g., fuel assemblies, reflector blocks, etc.) in the core. In order to further improve its computational efficiency in pre-calculating the response library a new response function generation method is developed to compute the response functions for the composite coarse meshes made of a smaller set of unique lattices on the fly within the COMET's deterministic transport core sweep. The efficiency is achieved by eliminating a number of unique lattices that can be made up from the reduced set of unique meshes on the fly. The numerical process consists of the following steps. First, the boundary condition on composite coarse mesh boundaries is projected onto the expansion basis to compute the incident flux moments on external surfaces of all the basic (reduced set of unique) coarse meshes. Secondly, the deterministic sweeping solver in COMET is used to converge on the outgoing/incoming flux expansion moments crossing interfaces between the basic coarse meshes. Thirdly, the response functions for the composite coarse meshes are constructed as a superposition on the fly. The new response function generation method was tested on 88 composite coarse meshes consisting of CANDU fuel bundles and moderator blocks. It was found that response functions generated by the new method agree very well with those generated by direct Monte Carlo calculations. The average and maximum relative differences in the surface-to-surface response coefficients computed by the two methods are 0.10% and 0.20%, respectively. Similarly, the average and maximum relative differences in the response fission densities are 0.13% and 0.43%, respectively. These discrepancies are within one standard deviation of the stochastic uncertainties. The new method is five times faster than the original direct Monte Carlo method. The size of the response function library for the new method is five times smaller than that for the original method, leading to significantly less requirement for the computer hard drive space and memory. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Augmented Adam-Gibbs model for glass melt viscosity and configuration entropy as functions of temperature and composition

As the temperature of glass melt increases, its structure approaches the state of a simple liquid while the configuration entropy approaches a maximum value. We describe this gradual change using a power law function of inverse temperature. The Adam-Gibbs model for glass viscosity as a function of temperature and glass composition augmented in this way is greatly simplified when applied to common glass families occupying moderate composition regions, such as float glass or nuclear waste glasses, on which properties can be approximated as linear functions of composition. The parsimonious model thus obtained is preferable for use in optimizing glass formulation and mathematical modeling of glass melting and forming. For multicomponent glasses with N viscosity-affecting components, the augmented Adam-Gibbs model requires 2N + 3 adjustable parameters. The model efficacy is demonstrated by fitting the model to a viscosity-temperature-composition dataset for low-activity nuclear waste glasses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Microstructure characterisation and mechanical properties of a functionally-graded NbC/high chromium white cast iron composite

Highlights: • A functionally-graded NbC – white cast iron composite was centrifugally cast. • Primary NbC particle distribution follows Stokes' Law, with 30 vol% at the surface. • Presence of primary NbC particles refined eutectic M{sub 7}C{sub 3} morphology at the surface. • The surface layer was hard and wear resistant, while the interior was tougher. • NbC and M{sub 7}C{sub 3} carbides form independent eutectic structures within the interior. - Abstract: A functionally graded NbC – high chromium white cast iron composite was successfully fabricated by centrifugal casting for high wear applications. The migration of primary NbC particles to the outer periphery, as predicted by Stokes' law, resulted in an extremely hard outer layer at the surface of a softer bulk material. Microstructural characterisation showed that both the volume fraction and the morphology of the carbides varies along the thickness of the specimen. At the outer surface, the NbC was present as primary carbides while Chinese-script NbC was found in the bulk of the material. Hardness, sliding wear and three-point bending tests confirmed that the outer layer was harder and more wear resistant than the rest of the material, which was correspondingly tougher. The study of the fracture surface of the specimens showed that there is a strong bond between NbC and the matrix such that delamination between the reinforcements and the matrix did not occur during fracture. If Chinese-script NbC can be reduced or prevented in the bulk material, further improvements to toughness could be achieved.

36 MATERIALS SCIENCE↗

LDRD 19A42-015, Multi-Wire Arc Additive Manufacturing

Additive manufacturing (AM) techniques can efficiently and cost-effectively fabricate components with both geometrical and compositional complexities, where functionally-graded compositions in a component allow multiple service requirements to be simultaneously addressed, such as corrosion and high temperature structural requirements. High cost alloy compositions need only be deposited in local areas where they are needed. A multi-wire arc additive manufacturing (m-WAAM) system was developed to enable functionally-graded, additively manufactured complex structures. The m-WAAM system utilizes multiple filler wire alloys, allowing control of composition and composition gradients in the component during additive fabrication. Ultimately, this project successfully developed a high deposition rate, arc-based, additive manufacturing process with the truly novel capability of enabling spatial composition tailoring during the build of the component. System capabilities and process science will be studied in a follow-on LDRD starting next year.

36 MATERIALS SCIENCE↗

Illuminating the pathways to carbon liberation: a systems approach to characterizing the consequential unknowns of carbon transformation and loss from thawing permafrost peatlands (Final Report)

The IsoGenie3 Project delivered new systems-level insights into carbon cycling in thawing permafrost landscapes, with an emphasis on methane and carbon dioxide emissions. From >200 samples from the site collected over a decade, co-analyzed for geochemistry and microbiology, the team recovered ~1,500 assembled microbial genomes and ~1,900 viral population genomes, revealing appreciable genetic novelty - from a new highly abundant bacterial phylum, to novel methane consumers and their activities, to rampant viral novelty. IsoGenie3 linked these organisms to carbon compound transformations (which define the cycling of organic matter in soils, and the loss of the greenhouse gases carbon dioxide and methane), and saw that the microbes at each stage of permafrost thaw had different genetic potential to degrade categories of compounds, expressed that genetic potential differently, and actually transformed carbon compounds into greenhouse gases in different ways. IsoGenie 3 identified that some of the thaw-stage differences were due to plant-microbiome relationships; the plant species across the thaw gradient contributed different carbon compounds into the soil, and hosted distinct microbiota (differing among parts of plants as well as species). Lastly, microbes in the saturated post-thaw conditions appeared likely to contribute to the mobilization and toxification of mercury released during thaw. In parallel with ongoing field sampling and analysis, hypotheses arising from field observations were tested via lab incubation experiments. When communities are taken out of their native habitats, they behave differently, and the team first rigorously quantified the magnitude of this effect on microbiome composition and functional capacity, organic matter composition, and gas production; overall the main system processes were maintained in the lab incubations under the conditions tested. Further, the microbial data could inform geochemical reaction network models of those processes. Then, the team ran experiments with additions of compounds, varying temperature, and “live” vs. “dead” peat (the latter having been gamma irradiated, with a few additional variants to control for methodological artifacts). From these, we (a) determined the importance of plant-derived soluble phenolic compounds in bogs’ extraordinary recalcitrance of organic matter, and carbon gas emissions skewed to carbon dioxide; (b) proposed an abiotic ‘tanning’ mechanism, which could contribute to Sphagnum’s inhibitory effect on anaerobic decomposition through alteration of N availability. IsoGenie3 illuminated longer-term and landscape-scale interactions of permafrost thaw and carbon cycling, advancing knowledge of the drivers of methane dynamics not only across in the permafrost-associated peatland (where hydrology and plant communities dictate microbiomes) but also their interconnected lakes (where sediment carbon quality and resident microbiota are determined by position within lake, and lake features). By leveraging observations of site methane dynamics extending well before this project, the team was able to construct a 44-year portrait of the interplay of permafrost thaw, hydrology, vegetation dynamics, and carbon gas emissions, and the doubling of the fully-thawed fens over this time. From the detailed study of this focal site, IsoGenie3 also aimed to improve model representation of these kinds of sites and processes. To improve predictions of methane transformations, we incorporated acetate and isotope dynamics into the ‘DNDC’ biogeochemistry model. In addition, recovered genomes were grouped into ‘functional groups’, i.e. the genomes that perform a specific function of interest, then used to parameterize maximum growth rate and optimum growth temperature (via signatures in their sequence composition) for the BioCrunch model. The BioCrunch model was then in turn used to test the impact of increasing functional resolution of the microbes, on the carbon gas emissions. Lastly for modeling, the ecosys model was parameterized from the microbial and other data, and used to evaluate drivers of e.g. change in methane emissions. Finally, this project also led to the development of a range of new methods and tools, a new metric of organic matter decomposability, as well as a graph-database solution to multidisciplinary data storage and querying. This project’s ongoing analyses at our focal site also contributed to broader advancements in understanding elements of genetic plasticity and methane metabolism, climate change microbiology and community assembly, global peatland geochemistry and Arctic lakes’ roles in climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗